Fintech Valuation Multiples Database: Mid-2025 Update




Fintech Valuation Multiples Database: Mid-2025 Update
Fintech Startup Valuation Multiples: Mid-2025 Edition
360 fintech companies across 9 verticals. Public comps, private rounds, and M&A transactions. Benchmarked by niche, stage, and deal type for the valuation conversations that matter.
Who this is for
This dataset is the right fit if you are pricing a fintech fundraising round and need real comps, benchmarking a deal for an IC memo, building a financial model with market-grounded assumptions, or evaluating a fintech acquisition and need to understand how vertical positioning affects pricing.
What is inside
360 companies across 9 fintech verticals Lending and Credit, Payments, Digital Banking, Crypto and Blockchain, InsurTech, Capital Markets, RegTech, SMB Tools, and WealthTech -- organized so you can filter to the subset that resembles your company.
Three company types in one database Public comps, private startup transactions, and M&A exits in a single structured file. Early stage through Series F and beyond.
Fields that support real valuation work EV, revenue, EBITDA where available, capital raised, round stage, implied multiples (EV/Revenue, EV/EBITDA, EV/Funding), and structured notes.
Stage-by-stage multiple analysis See how multiples shift from Seed through late-stage growth -- where pricing peaks, where it compresses, and what drives the difference.
Pre-built charts and summary views Charts and pivot-ready tables included. Drop it into your analysis or investor materials without reformatting.
How teams use it
Teams use this dataset to benchmark valuation ranges before a fundraising process, build comparable sets for IC memos and investor updates, pressure-test revenue multiple assumptions in financial models, and understand how fintech vertical positioning affects pricing.
What makes this different
Most fintech multiples you find online average across the entire sector. This database separates Payments companies from RegTech from Crypto because those businesses price completely differently. A Seed-stage lending platform should not be benchmarked against a public digital bank. The structure here makes sure it is not.
It is not a PDF report. It is a working tool built the same way Finro builds benchmarks for live valuation and financial modeling engagements.
FAQ
What format does the dataset come in? A structured Excel spreadsheet compatible with Excel and Google Sheets.
What is the data period? Mid-2025. This is a point-in-time snapshot reflecting market conditions and transactions available as of publication.
Can I use this for client work? Yes, single-user license for professional use. Contact us before purchasing if you need a team license.
Is there a more recent version coming? Finro publishes updated datasets on an ongoing basis. Check the store for the latest edition.
Looking for a different sector? Finro also publishes multiples databases for AI, EdTech, Cybersecurity, and PropTech. Browse all datasets.
Want more context before purchasing? Read the latest Fintech valuation analysis here.
This is a non-refundable digital product. The information provided in this document is for informational purposes only and should not be regarded as investment advice or a recommendation regarding any particular security or course of action. Neither, Finro Limited (“Finro”) nor any of its affiliates makes any representation or warranty or guarantee as to the completeness, accuracy, timeliness or suitability of any information contained within any part of the Report nor that it is free from error.
Finro does not accept any liability (whether in contract, tort or otherwise howsoever and whether or not they have been negligent) for any loss or damage (including, without limitation, loss of profit), which may arise directly or indirectly from use of or reliance on such information. Information in this report was obtained from publicly available sources, information obtained from the client or Finro’s internal analysis, projections and estimations.
Please read the full disclaimer in the spreadsheet before using the data.
